In today's world of electronic communication and commerce, the ability to identify a person for the purposes of security in remote transactions is paramount. A common form of security is a simple password, which, for example, is entered when a user wishes to access a computer network, or a personal identification card, which is widely used in, for example, bank automatic teller machines. Another way of ensuring the identity of a user is to capture and encode a biometric from the party and compare the result with a previously stored, or enrolled, result, for example stored on a remote database system. A biometric, for the present purposes, is a statistical or quantitative measure of a biological feature of a person. A robust biometric is one which can be used reliably and repeatedly to identify a person.
The best known robust biometric, used for identification purposes, is a fingerprint. Fingerprint analysis is amongst the most widely used and studied biometric techniques. The many new and exciting developments, which have taken place in the field of fingerprint science, are for example summarized in the monograph Advances in Fingerprint Technology, 2nd ed., edited by H. C. Lee and R. E. Gaensslen (CRC Press, 2001).
Typically in electronic fingerprint matching, a live fingerprint is scanned and electronically digitized. The digitized data generally contains information pertaining to characteristic features of the fingerprint, such as ridge endings, points of ridge bifurcation, and the core of a whorl, i.e. fingerprint minutiae. The digitized data is then analyzed and compared with stored data relating to fingerprints that have been obtained previously from corresponding authorized persons, i.e. fingerprint templates. When a match is detected, within a predetermined level of security in the form of a predetermined false acceptance rate, the individual is identified and a corresponding action is performed.
There exist many different devices, which are used in sensing the image of a human fingerprint, like optical systems as described for example in U.S. Pat. No. 5,109,427 to Yang, dated Apr. 28, 1992, in U.S. Pat. No. 5,187,748 to Lee, dated Feb. 16, 1993, or in U.S. Pat. No. 5,233,404 to Lougheed et al., dated Aug. 3, 1993, or capacitive contact imaging devices, as described for example in U.S. Pat. No. 4,353,056 to Tsikos, dated Oct. 5, 1982, in U.S. Pat. No. 5,325,442 to Knapp, dated Jun. 28, 1994, or in U.S. Pat. No. 6,333,989 to Borza, dated Dec. 25, 2001.
Different imaging devices usually provide sensed image data in different formats, the formats being most appropriate to the particular features of said imaging devices. On the other hand, the different software solutions developed for the analysis of fingerprint minutiae expect the data to be analyzed to obey certain predefined format specifications. In many cases, well-established analysis and authentication programs are restricted to the use of a particular hardware implementation of a biometric sensor. Also, different biometric sensors often operate only with one specific software implementation of an analysis and authentication method.
It would be highly advantageous to provide a system, which comprises a standardized, but flexible data interface, so that the data transfer from the biometric imaging device to the analysis software occurs according to user specified parameters. This way, it is possible that many different analysis and authentication software can use a same biometric sensing device.